Abstract
Background: Recent studies have addressed the possible role of long non-coding RNAs lnc-RNAs), Metastasis-Associated Lung Adenocarcinoma Transcript 1 (MALAT1), and Taurine Upregulated Gene 1 (TUG1), in modulating the underlying mechanisms of obesity-related metabolic abnormalities. However, studies are limited and contradictory. Hence, we sought to investigate the relationship of the transcript level of these two lnc-RNAs with metabolic syndrome (MetS)-related parameters in women with obesity and overweight.
Method: This cross-sectional study was conducted on 342 women with obese and overweight. We conducted assessments encompassing anthropometric measurements, body composition analysis, fasting blood sugar (FBS) levels, lipid profile analysis, insulin levels, HOMA-IR index, and liver enzyme profiling. A quantitative real-time polymerase chain reaction (PCR) was used to evaluate transcript levels of MALAT1 and TUG1. Also, a 147-question semi-quantitative food frequency questionnaire (FFQ) and the International Physical Activity Questionnaire (IPAQ) were used to evaluate food intake and physical activity, respectively.
Results: There was a significant association between FBS and MALAT1 transcript level (β: 0.382; 95% CI: 0.124, 0.640; P = 0.004). Also, there was a significant association between triglyceride (TG) and MALAT1 transcript level (β: 4.767; 95% CI: 2.803, 6.731; P < 0.0001). After adjusting for age, BMI, energy intake, and physical activity, an inverse significant association was observed between high-density lipoprotein cholesterol (HDL-c) and MALAT1 transcript level (β: -0.325; 95% CI: -0.644, -0.006; P = 0.046).
Conclusions: Our findings indicated positive associations between mRNA levels of MALAT1 and MetS-related parameters, including FBG, TG, HDL, and systolic blood pressure in overweight and obese women. However, large prospective studies are needed to further establish this concept.
Method: This cross-sectional study was conducted on 342 women with obese and overweight. We conducted assessments encompassing anthropometric measurements, body composition analysis, fasting blood sugar (FBS) levels, lipid profile analysis, insulin levels, HOMA-IR index, and liver enzyme profiling. A quantitative real-time polymerase chain reaction (PCR) was used to evaluate transcript levels of MALAT1 and TUG1. Also, a 147-question semi-quantitative food frequency questionnaire (FFQ) and the International Physical Activity Questionnaire (IPAQ) were used to evaluate food intake and physical activity, respectively.
Results: There was a significant association between FBS and MALAT1 transcript level (β: 0.382; 95% CI: 0.124, 0.640; P = 0.004). Also, there was a significant association between triglyceride (TG) and MALAT1 transcript level (β: 4.767; 95% CI: 2.803, 6.731; P < 0.0001). After adjusting for age, BMI, energy intake, and physical activity, an inverse significant association was observed between high-density lipoprotein cholesterol (HDL-c) and MALAT1 transcript level (β: -0.325; 95% CI: -0.644, -0.006; P = 0.046).
Conclusions: Our findings indicated positive associations between mRNA levels of MALAT1 and MetS-related parameters, including FBG, TG, HDL, and systolic blood pressure in overweight and obese women. However, large prospective studies are needed to further establish this concept.
| Original language | English |
|---|---|
| Pages (from-to) | 917-929 |
| Number of pages | 13 |
| Journal | Journal of Diabetes and Metabolic Disorders |
| Volume | 23 |
| Issue number | 1 |
| Early online date | 19 Dec 2023 |
| DOIs | |
| Publication status | Published - Jun 2024 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive licence to Tehran University of Medical Sciences 2023.
Funder
This study was supported by grants from the Tehran University of Medical Sciences, Tehran, Iran (Grant number: 1400-3-212-56212).Funding
This study was supported by grants from the Tehran University of Medical Sciences, Tehran, Iran (Grant number: 1400-3-212-56212).
| Funders | Funder number |
|---|---|
| Tehran University of Medical Sciences | 1400-3-212-56212 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- MALAT1
- Metabolic syndrome
- Obesity
- TUG1
- Long non-coding RNAs
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